Endomorphins: Promising Endogenous Opioid Peptides for the Development of Novel Analgesics.

Endomorphin-1 (EM1) and endomorphin-2 (EM2) are two endogenous ligands that belong to the opioid peptide family and have the highest affinity and selectivity for the µ-opioid receptor (MOR). The neuroanatomical distribution, ultrastructural features and neural circuitry of EM-containing neuronal structures have been morphologically demonstrated. In addition, the modulation effects of the EMs in different areas reflect their potential endogenous roles in many major physiological processes, including their remarkable roles in the transmission and modulation of noxious information. The distinguished antinociceptive property of the EMs in acute and chronic pain, including neuropathic pain, cancer pain and inflammatory pain, has been revealed and investigated for therapeutic purposes. However, EMs exert adverse effects in the gastrointestinal, urinary, cardiovascular, and respiratory systems, which impede the development of EMs as new analgesics. Numerous studies have synthesized and investigated EM analogues and demonstrated that these EM derivatives had improved pharmacological properties, supporting their therapeutic perspectives. In the present review, the results of previous studies, particularly morphological and pharmacological studies, were summarized. Finally, EM modifications and their potential clinical implications were described. Applying this knowledge about EMs may provide information for further investigations in clinical application.

Electromagnetic Source Imaging via a Data-Synthesis-Based Convolutional Encoder-Decoder Network.

Electromagnetic source imaging (ESI) requires solving a highly ill-posed inverse problem. To seek a unique solution, traditional ESI methods impose various forms of priors that may not accurately reflect the actual source properties, which may hinder their broad applications. To overcome this limitation, in this article, a novel data-synthesized spatiotemporally convolutional encoder-decoder network (DST-CedNet) method is proposed for ESI. The DST-CedNet recasts ESI as a machine learning problem, where discriminative learning and latent-space representations are integrated in a CedNet to learn a robust mapping from the measured electroencephalography/magnetoencephalography (E/MEG) signals to the brain activity. In particular, by incorporating prior knowledge regarding dynamical brain activities, a novel data synthesis strategy is devised to generate large-scale samples for effectively training CedNet. This stands in contrast to traditional ESI methods where the prior information is often enforced via constraints primarily aimed for mathematical convenience. Extensive numerical experiments as well as analysis of a real MEG and epilepsy EEG dataset demonstrate that the DST-CedNet outperforms several state-of-the-art ESI methods in robustly estimating source signals under a variety of source configurations.

Ginsenoside Rd Ameliorates Auditory Cortex Injury Associated With Military Aviation Noise-Induced Hearing Loss by Activating SIRT1/PGC-1α Signaling Pathway.

Free radicals and oxidative stress play an important role in the pathogenesis of noise-induced hearing loss (NIHL). Some ginseng monomers showed certain therapeutic effects in NIHL by scavenging free radicals. Therefore, we hypothesized that ginsenoside Rd (GSRd) may exert neuroprotective effects after noise-induced auditory system damage through a mechanism involving the SIRT1/PGC-1α signaling pathway. Forty-eight guinea pigs were randomly divided into four equal groups (normal control group, noise group, experimental group that received GSRd dissolved in glycerin through an intraperitoneal injection at a dose of 30 mg/kg body weight from 5 days before noise exposure until the end of the noise exposure period, and experimental control group). Hearing levels were examined by auditory brainstem response (ABR) and distortion product otoacoustic emission (DPOAE). Hematoxylin-eosin and Nissl staining were used to examine neuron morphology. RT-qPCR and western blotting analysis were used to examine SIRT1/PGC-1α signaling and apoptosis-related genes, including Bax and Bcl-2, in the auditory cortex. Bax and Bcl-2 expression was assessed via immunohistochemistry analysis. Superoxide dismutase (SOD), malondialdehyde (MDA), and glutathione peroxidase (GSH-Px) levels were determined using a commercial testing kit. Noise exposure was found to up-regulate ABR threshold and down-regulate DPOAE amplitudes, with prominent morphologic changes and apoptosis of the auditory cortex neurons (p < 0.01). GSRd treatment restored hearing loss and remarkably alleviated morphological changes or apoptosis (p < 0.01), concomitantly increasing Bcl-2 expression and decreasing Bax expression (p < 0.05). Moreover, GSRd increased SOD and GSH-Px levels and decreased MDA levels, which alleviated oxidative stress damage and activated SIRT1/PGC-1α signaling pathway. Taken together, our findings suggest that GSRd ameliorates auditory cortex injury associated with military aviation NIHL by activating the SIRT1/PGC-1α signaling pathway, which can be an attractive pharmacological target for the development of novel drugs for NIHL treatment.